Abstract. Recent studies have indicated that the uncertainty in the global carbon cycle
may have a significant impact on the climate. Since state of the art models
are too computationally expensive for it to be possible to explore their
parametric uncertainty in anything approaching a comprehensive fashion, we
have developed a simplified system for investigating this problem. By
combining the strong points of general circulation models (GCMs), which
contain detailed and complex processes, and Earth system models of
intermediate complexity (EMICs), which are quick and capable of large
ensembles, we have developed a loosely coupled model (LCM) which can
represent the outputs of a GCM-based Earth system model, using much smaller
computational resources. We address the problem of relatively poor
representation of precipitation within our EMIC, which prevents us from
directly coupling it to a vegetation model, by coupling it to a precomputed
transient simulation using a full GCM. The LCM consists of three components:
an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere
coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon
cycle (an NPZD-type marine ecosystem model); a state of the art vegetation
model (Sim-CYCLE); and a database of daily temperature, precipitation, and
other necessary climatic fields to drive Sim-CYCLE from a precomputed
transient simulation from a state of the art AOGCM. The transient warming of
the climate system is calculated from MIROC-lite, with the global temperature
anomaly used to select the most appropriate annual climatic field from the
pre-computed AOGCM simulation which, in this case, is a 1% pa increasing
CO2 concentration scenario.

By adjusting the effective climate sensitivity (equivalent to the equilibrium
climate sensitivity for an energy balance model) of MIROC-lite, the transient
warming of the LCM could be adjusted to closely follow the low sensitivity
(with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By
tuning of the physical and biogeochemical parameters it was possible to
reasonably reproduce the bulk physical and biogeochemical properties of
previously published CO2 stabilisation scenarios for that model. As an
example of an application of the LCM, the behavior of the high sensitivity
version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also
demonstrated. Given the highly adjustable nature of the model, we believe
that the LCM should be a very useful tool for studying uncertainty in global
climate change, and we have named the model, JUMP-LCM, after the name of our
research group (Japan Uncertainty Modelling Project).